Use when main results pass result-to-claim (claim_supported=yes or partial) and ablation studies are needed for paper submission.
日本語の概要は準備中です。原文の説明を表示しています。
wanshuiyin/Auto-claude-code-research-in-sleep1.7万2026年10月7日 更新
無料GitHub で公開
analyze-results
Analyze ML experiment results, compute statistics, generate comparison tables and insights. Use when user says "analyze results", "compare", or needs to interpret experimental data.
含まれるファイル（1）
- SKILL.md1.6 KB
SKILL.md（原文）
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Analyze Experiment Results
Analyze: $ARGUMENTS
Workflow
Step 1: Locate Results
Find all relevant JSON/CSV result files:
- Check
figures/,results/, or project-specific output directories - Parse JSON results into structured data
Step 2: Build Comparison Table
Organize results by:
- Independent variables: model type, hyperparameters, data config
- Dependent variables: primary metric (e.g., perplexity, accuracy, loss), secondary metrics
- Delta vs baseline: always compute relative improvement
Step 3: Statistical Analysis
- If multiple seeds: report mean +/- std, check reproducibility
- If sweeping a parameter: identify trends (monotonic, U-shaped, plateau)
- Flag outliers or suspicious results
Step 4: Generate Insights
For each finding, structure as:
- Observation: what the data shows (with numbers)
- Interpretation: why this might be happening
- Implication: what this means for the research question
- Next step: what experiment would test the interpretation
Step 5: Update Documentation
If findings are significant:
- Propose updates to project notes or experiment reports
- Draft a concise finding statement (1-2 sentences)
Output Format
Always include:
- Raw data table
- Key findings (numbered, concise)
- Suggested next experiments (if any)
レビュー
まだレビューはありません。使ってみた感想をお寄せください。
同じリポジトリのスキル
概要と使いどころ
Use when main results pass result-to-claim (`claim_supported = yes` or `partial`) and ablation studies are needed for paper submission. A secondary Codex agent designs ablations from a reviewer's perspective; the local executor reviews feasibility and implements.
日本語の概要は準備中です。原文の説明を表示しています。
wanshuiyin/Auto-claude-code-research-in-sleep1.7万2026年10月7日 更新
alphaxiv
無料Quick single-paper lookup via AlphaXiv LLM-optimized summaries with tiered source fallback. Use when user says "explain this paper", "summarize paper", pastes an arXiv/AlphaXiv URL, or provides a bare arXiv ID for quick understanding - not for broad literature search.
日本語の概要は準備中です。原文の説明を表示しています。
wanshuiyin/Auto-claude-code-research-in-sleep1.7万2026年10月7日 更新
arxiv
無料Search, download, and summarize academic papers from arXiv. Use when user says "search arxiv", "download paper", "fetch arxiv", "arxiv search", "get paper pdf", or wants to find and save papers from arXiv to the local paper library.
日本語の概要は準備中です。原文の説明を表示しています。
wanshuiyin/Auto-claude-code-research-in-sleep1.7万2026年10月7日 更新
Autonomously improve a generated paper via GPT-6-Astra xhigh review → implement fixes → recompile, for 2 rounds. Use when user says "改论文", "improve paper", "论文润色循环", "auto improve", or wants to iteratively polish a generated paper.
日本語の概要は準備中です。原文の説明を表示しています。
wanshuiyin/Auto-claude-code-research-in-sleep1.7万2026年10月7日 更新
Autonomously improve a generated paper via Claude review through claude-review MCP → implement fixes → recompile, for 2 rounds. Use when user says "改论文", "improve paper", "论文润色循环", "auto improve", or wants to iteratively polish a generated paper.
日本語の概要は準備中です。原文の説明を表示しています。
wanshuiyin/Auto-claude-code-research-in-sleep1.7万2026年10月7日 更新